Assessing the long- and short-run asymmetrical effects of climate change on rice production: empirical evidence from India

In recent years, environmental change has arisen as a ubiquitous problem and gained environmentalist's attention across the globe due to its long-term harmful effects on agricultural production, food supply, water supply, and livelihoods of rural households. The present study aims to explore the asymmetrical dynamic relationship between climate change and rice production with other explanatory variables. Based on the time series data of India, covering the period 1991-2018, the current study applied the nonlinear autoregressive distributed lag (NARDL) model and Granger causality approach. The results of the NARDL reveal that mean temperature negatively affects rice production in the long run while positively affecting it in the short run. Furthermore, positive shocks in rainfall and carbon emission have negative and significant impacts on rice production in the long and short run. In comparison, negative rainfall shocks significantly affect rice production in the long and short run. Wald test confirms the asymmetrical relationship between climate change and rice production. The Granger causality test shows feedback effect among mean temperature, decreasing rainfall, increasing carbon emission, and rice production. While no causal relationship between increasing temperature and decreasing carbon emission. Based on the empirical investigations, some critical policy implications emerged. Toward sustainable rice production in India, there is a need to improve irrigation infrastructure through increasing public investment and to develop climate-resilient seeds varieties to cope with climate change. Along with, at the district level government should provide proper training to farmers regarding the usage of pesticides, the proper amount of fertilizers, and irrigation systems.

Automated summary

This study examines the asymmetrical dynamic relationship between climate change and rice production using the nonlinear autoregressive distributed lag (NARDL) model and Granger causality approach based on time series data from India. The findings indicate that mean temperature has a negative long-term impact on rice production but a positive short-term impact. Positive shocks in rainfall and carbon emission have negative and significant effects on rice production in both the long and short term, while negative rainfall shocks significantly affect rice production. The Wald test confirms the asymmetric relationship between climate change and rice production, and the Granger causality test reveals a feedback effect among mean temperature, decreasing rainfall, increasing carbon emission, and rice production, but no causal relationship between increasing temperature and decreasing carbon emission.